The Graphical Models Toolkit (GMTK) is a toolkit for rapidly prototyping statistical models using dynamic graphical models (DGMs) and dynamic Bayesian networks (DBNs). It can be used for speech and language processing, bioinformatics, activity recognition, and any time series application. It features exact and approximate inference, many built-in factors including dense, sparse, and deterministic conditional probability tables, native support for ARPA backoff-based factors and factored language models, parameter sharing, gamma and beta distributions, dense and sparse Gaussian factors, heterogeneous mixtures, deep neural network factors, and time-inhomogeneous trellis factors, arbitrary order embedded Markov chains, a GUI graph viewer, and much more.

jfuzzylite is a Java fuzzy logic control library. Its goal is to allow you to easily create fuzzy logic controllers in a few steps utilizing object-oriented programming without any third-party libraries.

UniModeling is a big data analytics tool for unified modeling and reasoning in outdoor and indoor spaces. It supports the construction of unified graph models of outdoor and indoor spaces and RFID deployments in these spaces. It enables probabilistic incorporation of RFID data, facilitating the tracking of moving objects and enables the search for them to be optimized. Also included are three reasoning applications that pertain to the positioning of RFID readers in outdoor and indoor spaces and the points of potential traffic (over)load in these spaces.

fuzzylite is a fuzzy logic control library. Its goal is to allow you to easily create fuzzy logic controllers in a few steps utilizing object-oriented programming without requiring any third-party libraries. qtfuzzylite is a Qt-based GUI for fuzzylite. Its goal is to allow you to visually design your fuzzylite controllers and interact with them in real time.

QSMM, the "QSMM State Machine Model", is a framework for development of non-deterministic intelligent state models and systems with spur-driven behavior. It includes low-level functions for generating optimal actions by the system and high-level functions for building multinode models. In a multinode model, nodes represent components of a system you develop which choose optimal actions using the framework and can correspond to entities external to the system and which behavior is to be learnt. A node can choose optimal actions based on a current node state which is either set manually by your program or is identified automatically by the framework. Probability profiles for a state transition matrix and an action emission matrix of the node can be specified using an assembler program with a user-defined instruction set.

FreeFuzzyTime is a time reasoner based on Fuzzy Temporal Constraint Networks (FTCN), which treats fuzzy temporal information efficiently. It can be integrated into applications for diagnosis. This is especially important in areas like Intensive Care Units, where patients' data are handled by a temporal database. FuzzyTime uses a structure which consists of three levels of abstraction. The upper layer is the user interface, where a translator transforms the expressions introduced by the user into temporal relations between temporal entities (points and intervals). The semantics of a user’s expressions are analyzed and stored in the intermediate layer, or temporal world. Finally, the bottom layer is based on the FTCN model.

BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize, and interact in the learning process of a Multi-Layer Perceptron (MLP) on tasks that have a 2D character. Tasks include the famous two-spirals task or classification of satellite image data.